The preparation of artificial receptors that bind ligands like proteins, peptides, carbohydrates, microbes, pollutants, pharmaceuticals, and the like with high sensitivity and specificity is an active area of research. None of the conventional approaches has been particularly successful; achieving only modest sensitivity and specificity mainly due to low binding affinity.
Antibodies, enzymes, and natural receptors generally have binding constants in the 108-1012 range, which results in both nanomolar sensitivity and targeted specificity. By contrast, conventional artificial receptors typically have binding constants of about 103 to 105, with the predictable result of millimolar sensitivity and limited specificity.
Several conventional approaches are being pursued in attempts to achieve highly sensitive and specific artificial receptors. These approaches include, for example, affinity isolation, molecular imprinting, and rational and/or combinatorial design and synthesis of synthetic or semi-synthetic receptors.
Such rational or combinatorial approaches have been limited by the relatively small number of receptors which are evaluated and/or by their reliance on a design strategy which focuses on only one building block, the homogeneous design strategy. Common combinatorial approaches form microarrays that include 10,000 or 100,000 distinct spots on a standard microscope slide. However, such conventional methods for combinatorial synthesis provide a single molecule per spot. Employing a single building block in each spot provides only a single possible receptor per spot. Synthesis of thousands of building blocks would be required to make thousands of possible receptors.
Further, these conventional approaches are hampered by the currently limited understanding of the principals which lead to efficient binding and the large number of possible structures for receptors, which makes such an approach problematic.
There remains a need for methods for detecting ligands and for detecting compounds that disrupt one or more binding interactions.